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高碳醇/膨胀石墨复合相变热沉多目标优化

侯煦 邢玉明 郝兆龙 王仕淞 侯天睿

侯煦, 邢玉明, 郝兆龙, 等 . 高碳醇/膨胀石墨复合相变热沉多目标优化[J]. 北京航空航天大学学报, 2021, 47(9): 1866-1873. doi: 10.13700/j.bh.1001-5965.2020.0341
引用本文: 侯煦, 邢玉明, 郝兆龙, 等 . 高碳醇/膨胀石墨复合相变热沉多目标优化[J]. 北京航空航天大学学报, 2021, 47(9): 1866-1873. doi: 10.13700/j.bh.1001-5965.2020.0341
HOU Xu, XING Yuming, HAO Zhaolong, et al. Multi-objective optimization of a high alcohol/expanded graphite composite PCM based heat sink[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(9): 1866-1873. doi: 10.13700/j.bh.1001-5965.2020.0341(in Chinese)
Citation: HOU Xu, XING Yuming, HAO Zhaolong, et al. Multi-objective optimization of a high alcohol/expanded graphite composite PCM based heat sink[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(9): 1866-1873. doi: 10.13700/j.bh.1001-5965.2020.0341(in Chinese)

高碳醇/膨胀石墨复合相变热沉多目标优化

doi: 10.13700/j.bh.1001-5965.2020.0341
基金项目: 

航空科学基金 20172851018

详细信息
    通讯作者:

    郝兆龙, E-mail: haozhaolong@buaa.edu.cn

  • 中图分类号: TQ051.5;TK124

Multi-objective optimization of a high alcohol/expanded graphite composite PCM based heat sink

Funds: 

Aeronautical Science Foundation of China 20172851018

More Information
  • 摘要:

    为解决高温工作环境下电子芯片的发热问题,设计采用相变材料(PCM)的控温模块,建立相变材料的控温模块模型。相变材料选择高碳醇/膨胀石墨复合材料。借助FLUENT软件进行数值模拟,探究在相同加热功率下,加热面积对控温时间的影响。对控温模块的几何尺寸进行参数分析,将数值模拟结果用于训练人工神经网络,实现对控温时间的预测。根据芯片发热功耗、芯片尺寸,通过NGSA-Ⅱ多目标优化算法优化控温模块几何尺寸,延长控温时间,降低模块质量。最终得到一系列非支配解集,可根据控温时间需求选择合适的模块尺寸设计。针对长宽为35.4 mm、发热功率为15 W的芯片进行控温模块优化设计。环境温度为80℃,温控目标小于90℃,控温时间180 s,优化后模块减重13.0%,模块内温度与液相分布也更均匀。

     

  • 图 1  控温模块的几何模型

    Figure 1.  Geometric model of heat sink module

    图 2  控温模块剖面结构

    Figure 2.  Sectional structure of PCM based heat sink module

    图 3  相变温控实验系统

    Figure 3.  Experimental system of phase change temperature control

    图 4  实验系统照片

    Figure 4.  Photo of experimental system

    图 5  实验与数值模拟的温度-时间曲线对比

    Figure 5.  Temperature versus time curves of comparative experiment and numerical simulation

    图 6  计算域网格划分

    Figure 6.  Computational domain mesh partition

    图 7  不同网格密度对应的芯片平均温度

    Figure 7.  Average temperature of chip for different mesh density

    图 8  本文采用的神经网络结构

    Figure 8.  Architecture of neural network employed in present study

    图 9  NSGA-Ⅱ多目标优化算法流程

    Figure 9.  Steps involved in NSGA-Ⅱ malti-objective optimizazion algorithm

    图 10  优化后的Pareto前沿与优化前的结果对比

    Figure 10.  Comparison of Pareto front before and after optimization

    图 11  控温100 s后控温模块内部温度和液相分布

    Figure 11.  Temperature and liquid phase fraction distribution in the heat sink at 100 s

    表  1  数值模拟芯片-控温模块组合的几何尺寸

    Table  1.   Geometric dimension for chip-heat sink configuration for numerical simulation

    芯片边长c/mm 模块边长l/mm 厚度H/mm
    50 50 9~13
    35.4 50 9~13
    35.4 35.4 9~13
    28.9 50 9~13
    28.9 28.9 9~13
    下载: 导出CSV

    表  2  物性参数

    Table  2.   Parameters of physical properties

    材料 高碳醇 膨胀石墨
    密度/(kg·m-3) 920
    比热/(J·(kg·K)-1) 3 000 620 2 719
    导热系数/(W·(m·K)-1) 0.3 698 871
    潜热/(kJ·kg-1) 200 229.52 202.4
    相变温度/K 358
    下载: 导出CSV

    表  3  优化前后的模块几何尺寸对比

    Table  3.   Comparison of heat sink dimension before and after optimization

    参数 优化后 优化前
    c/mm 35.4 35.4
    P/W 15 15
    l/mm 42.5 50
    H/mm 15 12
    m/g 45.64 52.47
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-07-14
  • 录用日期:  2020-09-04
  • 网络出版日期:  2021-09-20

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